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Optimization of Injection-Molding Process with Genetic Algorithms

机译:用遗传算法进行注塑成型过程的优化

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Injection molding is widely used for mass production of polymer products. One important issue is how to determine the gate location(s) and process conditions to produce parts of the best quality. The objective of this paper is to develop an efficient optimization system that can automatically make such determination. The Genetic Algorithm (GA) will be compared with a functional search method, Simulated Annealing (SA) algorithm. The principle of both algorithms will be described and illustrated with examples. Application of these algorithms to determine gate location and optimal process condition in injection molding will be demonstrated with examples. Gate location is determined based on the principle of balanced flow paths, while the optimal process condition is computed by minimizing the warpage across the entire part. Results show that the Genetic Algorithm is more efficient computationally than the SA algorithm.
机译:注塑成型广泛用于聚合物产物的大规模生产。一个重要问题是如何确定门位置和过程条件,以产生最佳质量的部分。本文的目的是开发一种有效的优化系统,可以自动进行这种确定。将与函数搜索方法,模拟退火(SA)算法进行比较遗传算法(GA)。将用示例描述和说明这两种算法的原理。这些算法在注射成型中确定栅极位置和最佳过程条件将用实例说明。基于平衡流路径的原理确定栅极位置,而通过最小化整个部分的翘曲来计算最佳处理条件。结果表明,基因算法比SA算法更有效。

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